CGSharing: Efficient content sharing in GPU-based cloud gaming

Abstract

With the fast development of the GPU server technology, cloud gaming has become popular in recent years. Unlike the traditional desktop gaming where the graphic rendering is performed locally using the user's personal graphics card, cloud gaming runs multiple games to support many users at the same time in the data center where most of the rendering jobs are done in the remote GPU cluster. The rendered frames are streamed to user's devices such as notebooks, tablets and cell phones. For the economic cloud gaming to be viable, the operator must make full utilization of the expensive hardware resources like the graphic cards, and the state of art technology tries to render multiple instances of games on the same GPU. In this paper, we first identify that there are many redundant and duplicated contexts/workloads existing in today's cloud gaming rendering that waste a large amount of memory bandwidth and system energy. We in turn propose novel system architecture enhancements to effectively share the contents across the game instances from different users in the cloud gaming center.